25 citations · 100 across the 18 of their papers we have counts for
18 papers
Beyond Correlation: Refutation-Validated Aspect-Based Sentiment Analysis for Explainable Energy Market Returns
Wihan van der Heever, Keane Ong, Ranjan Satapathy +1
This paper proposes a refutation-validated framework for aspect-based sentiment analysis in financial markets, addressing the limitations of correlational studies that cannot disti…
Beyond I'm Sorry, I Can't: Dissecting Large Language Model Refusal
Nirmalendu Prakash, Yeo Wei Jie, Amir Abdullah +3
Refusal on harmful prompts is a key safety behaviour in instruction-tuned large language models (LLMs), yet the internal causes of this behaviour remain poorly understood. We study…
Mitigating Jailbreaks with Intent-Aware LLMs
Wei Jie Yeo, Ranjan Satapathy, Erik Cambria
Despite extensive safety-tuning, large language models (LLMs) remain vulnerable to jailbreak attacks via adversarially crafted instructions, reflecting a persistent trade-off betwe…
Understanding Refusal in Language Models with Sparse Autoencoders
Wei Jie Yeo, Nirmalendu Prakash, Clement Neo +3
Refusal is a key safety behavior in aligned language models, yet the internal mechanisms driving refusals remain opaque. In this work, we conduct a mechanistic study of refusal in…
Debiasing CLIP: Interpreting and Correcting Bias in Attention Heads
Wei Jie Yeo, Rui Mao, Moloud Abdar +2
Multimodal models like CLIP have gained significant attention due to their remarkable zero-shot performance across various tasks. However, studies have revealed that CLIP can inadv…
ESGSenticNet: A Neurosymbolic Knowledge Base for Corporate Sustainability Analysis
Keane Ong, Rui Mao, Deeksha Varshney +5
Evaluating corporate sustainability performance is essential to drive sustainable business practices, amid the need for a more sustainable economy. However, this is hindered by the…
SusGen-GPT: A Data-Centric LLM for Financial NLP and Sustainability Report Generation
Qilong Wu, Xiaoneng Xiang, Hejia Huang +5
The rapid growth of the financial sector and the rising focus on Environmental, Social, and Governance (ESG) considerations highlight the need for advanced NLP tools. However, open…
Towards Faithful Natural Language Explanations: A Study Using Activation Patching in Large Language Models
Wei Jie Yeo, Ranjan Satapathy, Erik Cambria
Large Language Models (LLMs) are capable of generating persuasive Natural Language Explanations (NLEs) to justify their answers. However, the faithfulness of these explanations sho…
Explainable Natural Language Processing for Corporate Sustainability Analysis
Keane Ong, Rui Mao, Ranjan Satapathy +4
Sustainability commonly refers to entities, such as individuals, companies, and institutions, having a non-detrimental (or even positive) impact on the environment, society, and th…
Self-training Large Language Models through Knowledge Detection
Wei Jie Yeo, Teddy Ferdinan, Przemyslaw Kazienko +2
Large language models (LLMs) often necessitate extensive labeled datasets and training compute to achieve impressive performance across downstream tasks. This paper explores a self…
How Interpretable are Reasoning Explanations from Prompting Large Language Models?
Wei Jie Yeo, Ranjan Satapathy, Rick Siow Mong Goh +1
Prompt Engineering has garnered significant attention for enhancing the performance of large language models across a multitude of tasks. Techniques such as the Chain-of-Thought no…
Plausible Extractive Rationalization through Semi-Supervised Entailment Signal
Wei Jie Yeo, Ranjan Satapathy, Erik Cambria
The increasing use of complex and opaque black box models requires the adoption of interpretable measures, one such option is extractive rationalizing models, which serve as a more…
A Comprehensive Review on Financial Explainable AI
Wei Jie Yeo, Wihan van der Heever, Rui Mao +3
The success of artificial intelligence (AI), and deep learning models in particular, has led to their widespread adoption across various industries due to their ability to process…
Recent Developments in Recommender Systems: A Survey
Yang Li, Kangbo Liu, Ranjan Satapathy +2
In this technical survey, we comprehensively summarize the latest advancements in the field of recommender systems. The objective of this study is to provide an overview of the cur…
FinXABSA: Explainable Finance through Aspect-Based Sentiment Analysis
Keane Ong, Wihan van der Heever, Ranjan Satapathy +2
This paper presents a novel approach for explainability in financial analysis by deriving financially-explainable statistical relationships through aspect-based sentiment analysis,…
Polarity and Subjectivity Detection with Multitask Learning and BERT Embedding
Ranjan Satapathy, Shweta Pardeshi, Erik Cambria
Multitask learning often helps improve the performance of related tasks as these often have inter-dependence on each other and perform better when solved in a joint framework. In t…
Can a Humanoid Robot be part of the Organizational Workforce? A User Study Leveraging Sentiment Analysis
Nidhi Mishra, Manoj Ramanathan, Ranjan Satapathy +2
Hiring robots for the workplaces is a challenging task as robots have to cater to customer demands, follow organizational protocols and behave with social etiquette. In this study,…
PhonSenticNet: A Cognitive Approach to Microtext Normalization for Concept-Level Sentiment Analysis
Ranjan Satapathy, Aalind Singh, Erik Cambria
With the current upsurge in the usage of social media platforms, the trend of using short text (microtext) in place of standard words has seen a significant rise. The usage of micr…